SOURCE-LINKED INTELLIGENCE

LentEx: Generalizable Latent Entity Extraction via Synthetic Data and Instruction-Tuned LLMs

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Latent entity extraction (LEE) tackles the challenge of identifying implicit, contextually inferred entities within free text-an area where traditional entity extraction methods fall short. In this paper, we introduce LentEx, a novel framework for latent entity extraction that leverages synthetic data generation and instruction fine-tuning to optimize smaller, efficient large language models (LLMs). Latent entities, which are often abstract and thematic, are crucial for applications such as retrieval-augmented generation (RAG), customer persona analysis, and knowledge graph enrichment. LentEx

Read original source ↗ Open in workspace

recordType

paper

region

Global